Impact of COMORBIDities After Radical Cystectomy Using a Predictive Method With Artificial Intelligence (COMORBID-AI)

  • STATUS
    Recruiting
  • End date
    Jan 22, 2024
  • participants needed
    500
  • sponsor
    Centre Hospitalier Universitaire, Amiens
Updated on 22 March 2022
radical cystectomy
bladder tumor

Summary

Clinician and the multidisciplinary team meeting in oncologic urology (MMO) play a key-role in the decision making. An unexplained surgeon attributable variance, probably linked to the subjective "eyeball test" effect, was identified as a strongest factor underlying non-compliance with guide line recommendations in the management of bladder cancer. So high-quality studies that identify barriers and modulators (such as comorbidities) of provider-level adoption of guidelines and how comorbidities are associated in making therapeutic choice and their impact in bladder cancer specific survival and overall survival, are crucial. To identify patients at high risk of early death, and to improve specific guideline for treatment might be decisive.

In order to assess survival, where mortality events compete, it will be more appropriate to compute a Cumulative Incidence Function (namely CIF). The investigators will compare outcomes across patient populations to obtain information to improve clinical decision-making. Such learning will be done through the use of neural networks or by applying population-based approaches, such as Genetic Algorithms (GA), Ant Colony Systems (ACS) and Particle Swarm Optimization (PSO), using as a four-stage based approach.

First, the investigators propose a "pretopology space" in order to study a dynamic phenomenon. Second, the investigators recall that the K-means approach remains one of the most used approaches for classifying a set of elements (patients / persons / others) into K (disjunctive) clusters. Third, the investigators propose a learning pretopology space for enhancing the clustering. Such an approach can be assimilated in spirit to one applied with high success on deep learning. Fourth and last, the investigators propose a reactive method that is able to include some new elements or remove some contained elements

Details
Condition Bladder Cancer, Comorbidity, Deep Learning
Clinical Study IdentifierNCT05204186
SponsorCentre Hospitalier Universitaire, Amiens
Last Modified on22 March 2022

Eligibility

Yes No Not Sure

Inclusion Criteria

years and older
Patient treated by radical cystectomy for bladder cancer

Exclusion Criteria

Computed tomography/magnetic resonance evidence of distant metastases
Clear my responses

How to participate?

Step 1 Connect with a study center
What happens next?
  • You can expect the study team to contact you via email or phone in the next few days.
  • Sign up as volunteer  to help accelerate the development of new treatments and to get notified about similar trials.

You are contacting

Investigator Avatar

Primary Contact

site

Additional screening procedures may be conducted by the study team before you can be confirmed eligible to participate.

Learn more

If you are confirmed eligible after full screening, you will be required to understand and sign the informed consent if you decide to enroll in the study. Once enrolled you may be asked to make scheduled visits over a period of time.

Learn more

Complete your scheduled study participation activities and then you are done. You may receive summary of study results if provided by the sponsor.

Learn more

Similar trials to consider

Loading...

Browse trials for

Not finding what you're looking for?

Every year hundreds of thousands of volunteers step forward to participate in research. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.

Sign up as volunteer

user name

Added by • 

 • 

Private

Reply by • Private
Loading...

Lorem ipsum dolor sit amet consectetur, adipisicing elit. Ipsa vel nobis alias. Quae eveniet velit voluptate quo doloribus maxime et dicta in sequi, corporis quod. Ea, dolor eius? Dolore, vel!

  The passcode will expire in None.
Loading...

No annotations made yet

Add a private note
  • abc Select a piece of text from the left.
  • Add notes visible only to you.
  • Send it to people through a passcode protected link.
Add a private note